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Intelligent Systems Development refers to the design, creation, and implementation of systems capable of performing tasks that would normally require human intelligence. In this context, it is specifically associated with the development of Gated Recurrent Units (GRUs) - a type of recurrent neural network architecture used for processing sequential data in deep learning models. GRUs are particularly effective at handling tasks involving temporal dynamics and contextual information, making them highly suitable for applications such as speech recognition, language modeling, and time-series prediction. Intelligent Systems Development for GRUs encompasses the entire lifecycle of these systems, from problem identification and data collection to model training and evaluation, deployment, and ongoing maintenance. By harnessing the power of deep learning techniques like GRUs, Intelligent Systems Development aims to create sophisticated, adaptive systems that can learn from experience, make informed decisions, and improve over time.